Elgarf Maha, Salam Hanan, Peters Christopher
Social Machines and Robotics Lab (SMART), Department of Computer Science, New York University in Abu Dhabi (NYUAD), Abu Dhabi, United Arab Emirates.
Embodied Social Agents Lab (ESAL), Department of Electrical Engineering and Computer Science (EECS), KTH Royal Institute of Technology, Stockholm, Sweden.
Front Robot AI. 2024 Dec 13;11:1457429. doi: 10.3389/frobt.2024.1457429. eCollection 2024.
Creativity is an important skill that is known to plummet in children when they start school education that limits their freedom of expression and their imagination. On the other hand, research has shown that integrating social robots into educational settings has the potential to maximize children's learning outcomes. Therefore, our aim in this work was to investigate stimulating children's creativity through child-robot interactions. We fine-tuned a Large Language Model (LLM) to exhibit creative behavior and non-creative behavior in a robot and conducted two studies with children to evaluate the viability of our methods in fostering children's creativity skills. We evaluated creativity in terms of four metrics: fluency, flexibility, elaboration, and originality. We first conducted a study as a storytelling interaction between a child and a wizard-ed social robot in one of two conditions: creative versus non-creative with 38 children. We investigated whether interacting with a creative social robot will elicit more creativity from children. However, we did not find a significant effect of the robot's creativity on children's creative abilities. Second, in an attempt to increase the possibility for the robot to have an impact on children's creativity and to increase the fluidity of the interaction, we produced two models that allow a social agent to autonomously engage with a human in a storytelling context in a creative manner and a non-creative manner respectively. Finally, we conducted another study to evaluate our models by deploying them on a social robot and evaluating them with 103 children. Our results show that children who interacted with the creative autonomous robot were more creative than children who interacted with the non-creative autonomous robot in terms of the fluency, the flexibility, and the elaboration aspects of creativity. The results highlight the difference in children's learning performance when inetracting with a robot operated at different autonomy levels (Wizard of Oz versus autonoumous). Furthermore, they emphasize on the impact of designing adequate robot's behaviors on children's corresponding learning gains in child-robot interactions.
创造力是一项重要技能，众所周知，当孩子开始接受限制其表达自由和想象力的学校教育时，他们的创造力会大幅下降。另一方面，研究表明，将社交机器人融入教育环境有可能使孩子的学习成果最大化。因此，我们这项工作的目的是研究通过儿童与机器人的互动来激发孩子的创造力。我们对一个大语言模型（LLM）进行了微调，使其在机器人中展现出创造性行为和非创造性行为，并与孩子们进行了两项研究，以评估我们的方法在培养孩子创造力技能方面的可行性。我们从流畅性、灵活性、详尽性和独创性这四个指标来评估创造力。我们首先进行了一项研究，让38名儿童在两种条件之一（创造性与非创造性）下与一个巫师风格的社交机器人进行讲故事互动。我们研究了与有创造性的社交机器人互动是否会激发孩子更多的创造力。然而，我们没有发现机器人的创造力对孩子的创造能力有显著影响。其次，为了增加机器人对孩子创造力产生影响的可能性，并提高互动的流畅性，我们制作了两个模型，分别允许一个社交主体在讲故事情境中以创造性方式和非创造性方式自主与人类互动。最后，我们进行了另一项研究，将我们的模型部署在一个社交机器人上，并对103名儿童进行评估，以评价我们的模型。我们的结果表明，在创造力的流畅性、灵活性和详尽性方面，与有创造性的自主机器人互动的孩子比与非创造性的自主机器人互动的孩子更有创造力。这些结果凸显了孩子在与处于不同自主水平（绿野仙踪模式与自主模式）的机器人互动时学习表现的差异。此外，它们强调了设计适当的机器人行为对儿童在儿童与机器人互动中相应学习收获的影响。
